Tan et al., 2017 - Google Patents

Enabling query processing across heterogeneous data models: A survey

Tan et al., 2017

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Document ID
4527655587917604463
Author
Tan R
Chirkova R
Gadepally V
Mattson T
Publication year
Publication venue
2017 IEEE International Conference on Big Data (Big Data)

External Links

Snippet

Modern applications often need to manage and analyze widely diverse datasets that span multiple data models [1],[2],[3],[4],[5]. Warehousing the data through Extract-Transform-Load (ETL) processes can be expensive in such scenarios. Transforming disparate data into a …
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Classifications

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    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G06F17/30424—Query processing
    • G06F17/30477—Query execution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06F17/30424—Query processing
    • G06F17/30442—Query optimisation
    • G06F17/30448—Query rewriting and transformation
    • G06F17/30451—Query rewriting and transformation of sub-queries or views
    • G—PHYSICS
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    • G06F17/30321—Indexing structures
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    • G06F17/30592—Multi-dimensional databases and data warehouses, e.g. MOLAP, ROLAP
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
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    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99934—Query formulation, input preparation, or translation

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